---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-subset
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# videomae-base-finetuned-ucf101-subset

This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7852
- Accuracy: 0.7857

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 380

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3762        | 0.1   | 38   | 1.4490          | 0.2857   |
| 1.2421        | 1.1   | 76   | 1.3190          | 0.4286   |
| 0.8753        | 2.1   | 114  | 0.9506          | 0.5714   |
| 0.4285        | 3.1   | 152  | 0.5580          | 0.7857   |
| 0.3808        | 4.1   | 190  | 0.4951          | 0.8571   |
| 0.1368        | 5.1   | 228  | 0.1578          | 0.9286   |
| 0.043         | 6.1   | 266  | 0.0475          | 1.0      |
| 0.0842        | 7.1   | 304  | 0.0624          | 1.0      |
| 0.003         | 8.1   | 342  | 0.0557          | 1.0      |
| 0.0828        | 9.1   | 380  | 0.0446          | 1.0      |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.19.1